Modern AI architectures may look radically new, but their power comes down to a deceptively simple principle: dynamic, programmable weights. What once seemed like a mathematical shortcut in LSTMs and Transformers turns out to mirror a fundamental mechanism of the human brain—how it computes and updates prediction errors.

Alzheimer’s disease disrupts brain networks and is marked by shifts in brain rhythms detectable by EEG long before significant cell death. Recognizing these changes is vital for early detection and targeted interventions.